Name
Abstract | ||
|---|---|---|
Clustered failure time data often arise in biomedical studies and a marginal regression modeling approach is often preferred to avoid assumption on the dependence structure within clusters. A novel estimating equation approach is proposed based on a semiparametric marginal proportional hazards model to take the correlation within clusters into account. Different from the traditional marginal method for clustered failure time data, our method explicitly models the correlation structure within clusters by using a pre-specified working correlation matrix. The estimates from the proposed method are proved to be consistent and asymptotically normal. Simulation studies show that the proposed method is more efficient than the existing marginal methods. Finally, the model and the proposed method are applied to a kidney infections study. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.csda.2015.01.012 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
estimating equation,marginal model | Econometrics,Cluster (physics),Proportional hazards model,Regression analysis,Correlation,Covariance matrix,Statistics,Mathematics,Estimating equations,Hazard ratio,Marginal model | Journal |
Volume | Issue | ISSN |
87 | C | 0167-9473 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yi Niu | 1 | 46 | 19.65 |
| Yingwei Peng | 2 | 38 | 14.54 |